كشف النشاط الصوتي القائم على اختبار التجانس
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منشور:
Jun 28, 2014
الكلمات المفتاحية:
كشف النشاط الصوتي، نموذجان ذوا ارتداد ذاتي، اختبار الفرضيات
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الملخص
في هذا العمل نقترح طريقة جديدة لكشف النشاط الصوتي ، ترتكز على اختبار تجانس نموذجين ذاتيي الارتداد ، يمثلان قطعتي اشارة كلامية، و ذلك بعد حساب مسافة معينة. يصاغ هذا الاختبار باعتباره يمثل اختبار فرضيات. يتم فيه تحديد عتبة، وفقا لاحتمال انذار كاذب معين.أعطت الاختبارات التي أجريت على قاعدة البيانات AURORA
نتائج مرضية مقارنة مع طرق أخرى
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كيفية الاقتباس
رقيقو., & جدوم. (2014). كشف النشاط الصوتي القائم على اختبار التجانس. AL-Lisaniyyat, 20(1), 77-85. https://doi.org/10.61850/allj.v20i1.506
القسم
Articles
المراجع
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Massaloux, D, Lamblin C. and Petit J-P., “Ttu-t recommendation g.729 annex b : A
silence compression scheme for use with g.729 optimized for v.70 digital simulta- neous voice and data applications. IEEE Communications Magazine, 35(9):64-73, September 1997. [15] European Standard (Telecommunications series). Voice activity detector (vad) for adaptive multi-rate (amr) speech trafic channels, 1999. ETSI EN 301 708 v7.11 standard description. [16] European standard (Telecomunications- nseries). Transmission and quality aspect
front-end feature extarction algorithm, 2007. ETSI ES 202050 standard descriprtion.
ple statistical models,” IEEE Trans Signal Processing, 2006, pp.1965-1976. [8] Morales-Cordovilla, JA, Ning Ma, Sanchez, V., Carmona, JL., Peinado,
A.M. and Barker, J., “A pitch based noise estimation technique for robust speech recognition with missing data,” Acous- tics, Speech and Signal Processing (ICASSP), 2011 IEEE International Con- ference on IEEE, 2011, pp. 4808—4811. [9] Rissanen J., “Modeling by shortest data description,” Automatica, vol.14, pp. 465—471, 1978. [10] Levinson N., “The Wiener RMS (Root Mean Square) error Criterion in filter de- sign and prediction,” J Math. Phys., vol. 25, 1947, pp. 261-278. [11] Martinez, R., Gomez, P., and Derouiche, K.,A test of homogeneity for auto- regressive processes ‘’, Int. J. Adapt. Control Signal Process. 2002; 16:213- 242. [12] Hirsch H. and Pearce D., “The Aurora experimental framework for the perfor- mance evaluation of speech recognition systems under noisy conditions.” ISCA ITRW ASR 2000, Paris, France, Septem- ber 18-20. [13] Sohn J., Kim N. S. and Sung W., “A
statistical model-based voice activity de- tection,” IEEE Signal Process. Lett., vol. 16, no. 1, pp. 1-3, Jan. 1999. [14] Benyassine A., Shlomot E..Su H.-Y.
Massaloux, D, Lamblin C. and Petit J-P., “Ttu-t recommendation g.729 annex b : A
silence compression scheme for use with g.729 optimized for v.70 digital simulta- neous voice and data applications. IEEE Communications Magazine, 35(9):64-73, September 1997. [15] European Standard (Telecommunications series). Voice activity detector (vad) for adaptive multi-rate (amr) speech trafic channels, 1999. ETSI EN 301 708 v7.11 standard description. [16] European standard (Telecomunications- nseries). Transmission and quality aspect
front-end feature extarction algorithm, 2007. ETSI ES 202050 standard descriprtion.